Latent Class Analysis of Respondent Scalability

Abstract

The psychometric literature contains many indices to detect aberrant respondents. A different, promising approach is using ordered latent class analysis with the goal to distinguish latent classes of respondents that are scalable, from latent classes of respondents that are not scalable (i.e., aberrant) according to the scaling model adopted. This article examines seven Latent Class models for a cumulative scale. A simulation study was performed to study the efficacy of different models for data that follow the scale model perfectly. A second simulation study was performed to study how well these models detect aberrant respondents.